secret-handling

To prevent AI agents from leaking secrets, enforce security policies that strictly block reading local development files like .env and restrict credentials from being written into version-controlled files. This ensures sensitive data remains isolated during automated codebase interactions.

To scan staged files for secrets, use pre-commit git hooks that automatically check file contents for sensitive patterns before allowing a commit. This validates staged changes and blocks violations by alerting on detected credentials or PII.

The best way to stop credentials from entering version-controlled files is to restrict output paths, preventing AI agents from writing passwords or PII into the .squad/ directory. This enforces data protection by blocking sensitive output at the source.

To remediate historical data leaks, follow structured remediation steps provided by the secret-handling policy to safely purge exposed credentials from git history. This guides you through removing sensitive patterns from prior commits to secure your repository.

Yes, this approach explicitly works with local development environment files by strictly prohibiting agents from reading .env files containing live credentials. This prevents accidental exposure of local secrets during AI-assisted coding sessions.

Yes, you can enforce compliance and AI safety policies automatically by applying pre-commit validation hooks that scan for secret patterns. This restricts AI agents from accessing sensitive files and blocks unauthorized commits, ensuring continuous data protection.